HackTheRounds Interview Experiences

xAI Software Engineer Interview Experience (2026) - Trie Word Search, LRU, Nested Transaction DB, Offer

xAI SWE loop: 15 min phone screen, 3 round onsite with Word Search II on a letter grid, LRU Cache implementation, and in memory DB with nested transactions desi

By Anonymous · 2026-04-15

Background

I did not expect xAI to call me back. I applied cold as a new grad with a mid-tier background and I figured the listing was performative. Then a recruiter pinged me three days later and the loop moved fast enough that I barely had time to prep. The whole feel is less FAANG playbook and more startup-with-a-lot-of-funding: tight phone screen, a compressed three-round onsite, and interviewers who cared more about thinking style than about textbook answers.

Timeline

Phone Screen (15 min)

The shortest screen I have ever done. The recruiter had a checklist and moved through it at conversational speed: describe your most technical project in 30 seconds, what are your two strongest languages, tell me about something you shipped to production in C++ or Python. About a dozen of these in ten minutes. The final five minutes was my turn to ask questions.

The trick is not to ramble. Every answer landed in under 45 seconds or the recruiter cut in. I practiced a 30-second version of my main project out loud before the call and that was the single best thing I did.

Virtual Onsite (3 rounds)

Round 1 — Nine-Square Letter Grid with Trie

Problem: Given an N x N board of letters and a dictionary of target words, return every dictionary word that can be constructed by following orthogonally adjacent cells, with no cell reused inside a single word. The board can be up to around 12 on a side and the dictionary can have thousands of entries.

I went with a trie of the dictionary plus DFS from every starting cell. The trie buys you the critical pruning: if the current path is not a prefix of anything remaining, backtrack immediately. Without it, DFS on a 12x12 grid with a long word list blows up. I also used a visited-set on the board path that gets restored on backtrack, and I deleted words from the trie as I found them to avoid duplicate reports and to shrink the search space progressively.

Runtime is roughly O(M N 4^L) where L is the max word length, but in practice trie pruning kills most branches early. The interviewer pushed on the "delete from trie" optimization and asked me to justify it on a worst-case input. I said it does not change the big-O, but it monotonically shrinks the prefix fan-out and is essentially free because you already walked the trie node.

This question is coming soon to HackTheRounds.

Round 2 — LRU Cache

Problem: Implement get(key) and put(key, value) with both operations running in O(1). Capacity is fixed at construction time.

Classic doubly linked list plus hash map. Map keys to list nodes, maintain head and tail sentinels, move a node to the head on access, evict from the tail on overflow. I wrote it fast, which turned out to be a mild trap because I forgot to update the tail pointer in one of my initial draft evictions. I caught it only because I ran my own test case before handing it back to the interviewer. That recovery was probably worth more than a flawless initial write.

The interviewer pushed a follow-up on thread safety. I said I would wrap the two operations in a single mutex for correctness, then noted that the real next step is to shard the cache by key hash so each shard has its own lock and contention drops roughly by the shard count. He nodded and moved on.

This question is coming soon to HackTheRounds.

Round 3 — In-Memory DB with Nested Transactions

Problem: Build an in-memory key-value store supporting SET(key, value) , GET(key) , BEGIN , ROLLBACK , and COMMIT . Transactions must nest: BEGIN inside a BEGIN starts a child, ROLLBACK undoes only the innermost, COMMIT flushes the innermost into its parent.

The data structure that solves this cleanly is a stack of dictionaries. The base store is the bottom dictionary. Each BEGIN pushes a new dictionary. SET writes into the top. GET walks the stack top to bottom and returns the first hit, treating a tombstone value as "deleted." ROLLBACK pops the top. COMMIT merges the top into the one below it and pops.

I coded the core in about 20 minutes and spent the rest of the round on follow-ups. The interviewer asked about durability (write-ahead log), concurrency (MVCC vs two-phase locking, I picked MVCC and explained why reads do not block writes), and horizontal scaling (consistent-hashing the key space and running a coordinator for cross-shard transactions using two-phase commit). The round was less about the initial code and more about whether I could reason flexibly about distributed data systems.

This question is coming soon to HackTheRounds.

Result

Offer with a comp package that leaned heavily on equity. The recruiter was direct about the fact that xAI expects you to work hard and that there is no pretense of a cushy FAANG pace. I appreciated the honesty.

Tips

  1. Prep a 30-second version of your best project. The phone screen rewards concision. If your default answer is two minutes, shorten it before the call or you will get cut off mid-sentence.
  2. For Round 1, build your trie to allow deletion. The "delete word on find" optimization is not just a micro-optimization, it is a signal to the interviewer that you have solved Word Search II in production, not just read the solution.
  3. Run your own LRU test before handing it in. The tail-pointer bug is the single most common failure mode in the LRU round. Write a 5-line test that puts, evicts, and peeks the tail before the interviewer asks.
  4. Know the stack-of-dicts pattern for nested transactions cold. Do not invent the structure during the interview. Walk in with it cached. The interesting part of the round is the follow-up on durability and concurrency, not the initial implementation.
  5. Have an MVCC versus 2PL opinion. The xAI system-design round will ask about concurrency control explicitly. Pick a side, justify it, and be ready to switch if the interviewer pushes.
  6. Treat xAI like a startup, not a FAANG. The interviewers care about whether you can think from first principles when a new problem shows up, not whether you memorized the LeetCode top 150. If you give rote answers you will get rote results.

The xAI loop is compressed and intense and the interviewers do not hold your hand, but if you can think out loud and iterate under pressure it is one of the more intellectually honest interviews in the industry. Good luck to anyone prepping.